Ascent Science SVM plugin

Standard support-vector classification backed by sklearn.svm.SVC.

python -m pip install ascent-science-svm==0.1.0

import ascent
model = ascent.machine_learning.SVMClassifier(kernel="rbf", C=1.0, gamma="scale")
model.fit(X, y)
predictions = model.predict(X_test)

Metadata

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Source distribution for ascent-science-svm 0.1.0
File	Size	Uploaded
ascent_science_svm-0.1.0.tar.gz	2.5 kB	Sep 23, 2026	Details

Table of built distributions (wheels) for ascent-science-svm 0.1.0
File	Interpreter	ABI	Platform	Reset
ascent_science_svm-0.1.0-py3-none-any.whl 2.9 kB Sep 23, 2026	Python 3	none	any	Details

Total release size: 5.4 kB

Download URL	ascent_science_svm-0.1.0.tar.gz
Size	2.5 kB
Tags	Source
SHA-256 checksum How to use checksums	`62600c90e28bc803205454cfb0b67b0bd1dd102f55cebbb4fc478eac49e6d922`
BLAKE2b-256 checksum How to use checksums	`931dbfd02fd25db11c0c2ae45fb3e7a26422219f8ffaee6fc3e75515a84c247e`
Upload date	Sep 23, 2026
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`twine/7.0.0 CPython/3.13.13`

Download URL	ascent_science_svm-0.1.0-py3-none-any.whl
Size	2.9 kB
Tags	Python 3
SHA-256 checksum How to use checksums	`11ed2a4fd1bb1ad93dd25914dc78fa4d1e69af749faddbb2bd52e9189ea29772`
BLAKE2b-256 checksum How to use checksums	`8b2b68ce4ccf58c987c5a154ce937e30aafd08cf33027056ef35424d9dab28b8`
Upload date	Sep 23, 2026
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`twine/7.0.0 CPython/3.13.13`

This release

0.1.0 This release